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Dependency Parsers for Persian
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
2012 (English)In: Proceedings of 10th Workshop on Asian Language Resources, COLING 2012, 24th International Conference on Computational Linguistics, Mumbai, India, Mumbai, India: ACL Anthology , 2012Conference paper, Published paper (Refereed)
Abstract [en]

We present two dependency parsers for Persian, MaltParser and MSTParser, trained on theUppsala PErsian Dependency Treebank. The treebank consists of 1,000 sentences today. Itsannotation scheme is based on Stanford Typed Dependencies (STD) extended for Persianwith regard to object marking and light verb contructions. The parsers and the treebank aredeveloped simultanously in a bootstrapping scenario. We evaluate the parsers by experimentingwith different feature settings. Parser accuracy is also evaluated on automatically generated andgold standard morphological features. Best parser performance is obtained when MaltParseris trained and optimized on 18,000 tokens, achieving 68.68% labeled and 74.81% unlabeledattachment scores, compared to 63.60% and 71.08% for labeled and unlabeled attachmentscore respectively by optimizing MSTParser.

Place, publisher, year, edition, pages
Mumbai, India: ACL Anthology , 2012.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-188781OAI: oai:DiVA.org:uu-188781DiVA, id: diva2:579165
Conference
24th International Conference on Computational Linguistics, 8-15 December, 2012, Mumbai, India
Available from: 2013-01-02 Created: 2012-12-19 Last updated: 2017-01-25Bibliographically approved

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CiteExportLink to record
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